Artificial Intelligence in 2024: A Thematic Analysis of Media Coverage

This thesis investigates how three agenda-setting U.S. newspapers — The New York Times, The Wall Street Journal, and The Washington Post — framed artificial intelligence (AI) during the year 2024. Using an inductive thematic analysis grounded in Braun and Clarke's six-phase procedure, 300 randomly-selected articles (100 per outlet) were analyzed and interpreted as media frames. Eight dominant frames emerged: AI Boom vs. Bubble, Misuse and Misinformation, Ethical and Moral Challenges, Policy and Governance, Societal and Cultural Impact, Work and Automation, Environmental Impact, and Technological Advancements and Future Risks. Across coverage, fear narratives centered on disinformation, job displacement, algorithmic bias, environmental costs, and existential risk. Results suggest that U.S. legacy media have moved beyond early techno-optimism towards a more nuanced discourse that simultaneously fuels investment and adoption, demands regulation and safeguards, and shapes public perception. These findings document how narratives evolve in response to rapid technological change and provide information for scholars, policymakers, and technologists seeking to understand how media discourse may steer AI governance and adoption.

Name thesis:degree_name

MACOM

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Communication

Department dc:contributor.department

Communication

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Williams, Luke

Chair dc:contributor.committeechair

• Myers, Marcus Cayce

Committee members dc:contributor.committeemember

• Kuypers, Jim A.
• Logan, Nneka

• framing theory
• thematic analysis
• artificial intelligence
• AI
• 2024

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:44170

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/134281